Stock market is anti-inductive: future performance takes into account your attempts at predicting it. Any regularity in the stop market disappears the moment someone spots it and starts trading on it.

Yeah models assume future data can be predicted with past data, which of course is not always true in real life due fundamental limitations of statistics, such as very fat tailed distributions in stock markets.

Competent data scientists must be able to spot those cases quickly.

Predicting stock marketperformance, i.e. performance of individual equities ?

The TL;DR answer is "no, but...".

No because by definition there is a high probability for individual equities to display idiosyncratic behaviour. Why ? Because we are, afterall, talking about individual companies. So their stockmarket performance is inherently tied to their corporate financial performance, their corporate prospects and how investors feel about all that jazz.

The "but" comes because there are, as always, exceptions to the rule.

You can, for example, engage in momentum trading. That should be (reasonably !) simple to model with a few inputs.

Otherwise, at the other end of the complexity spectrum, you can build a model to identify stocks that are in a macro regime. When stocks are in a macro regime it means that they are behaving as a proxy for macroeconomics instead of the individual usual corporate measures. This means you can build your model based on real quantitative measures (i.e. suitable macro factors) instead of trying to second guess idiosyncratic stock behaviour. The only real downside is that you will need access to quality macro data feeds, so if you are thinking of doing this as a retail investor (i.e. private individual) you might find yourself falling at the first hurdle.